Shape matching or object recognition is a fundamental problem in computer vision and has been used in various applications ranging from information retrieval to object tracking. The measurements of similarities between templates and target objects have been studied extensively. Human beings naturally recognize thousands if not millions of shapes instantly with no effort. The lightening, scale, orientation, or viewing direction in which an object is viewed is easily reconciled by the human mind. Computers, on the other hand, do not easily interpret shapes when appearances have been modified. Computer vision focuses on the identification of these shapes.
One area of particular interest in computer vision is occlusions. An occlusion is a partially obstructed object in the image. Because a portion of the object is not viewable in the image, the object shape and other properties have changes. Occlusions occur when one object is positioned in front of another. Occlusions may also occur when lighting for an object changes. For example, shadows may change the appearance of an object. An image of an object taken midday may be matched easily to a template but images of the same object taken later in the day may be too occluded by shadows for accurate matching. One particular area of concern is object recognition in aerial photographs of buildings, which tend to cast far reaching shadows.